Dynamic Modeling of Manufacturing Equipment Capability using Condition Information in Cloud Manufacturing

Wenjun Xu, Jiajia Yu, Zude Zhou, Yongquan Xie, Duc Pham, Chunqian Ji

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)
2 Downloads (Pure)


There is a growing need of knowledge description of manufacturing equipment and their capabilities for users, in order to efficiently obtain the on-demand services of manufacturing equipment in cloud manufacturing, and the understanding of the manufacturing capability of equipment is the most important basis for optimizing the cloud service management. During the manufacturing processes, a number of uncertain incidents may occur, which could degrade the manufacturing system performance or even paralyze the production line. Hence, all aspects about the equipment should be reflected within the knowledge description, and the static and dynamic information are both included in the knowledge model of manufacturing equipment. Unification and dynamics are the most important characteristics of the framework of knowledge description. The primary work of this study is fourfold. First, three fundamental ontologies are built, namely, basic information ontology, functional ontology, and manufacturing process ontology. Second, the correlation between the equipment ontology and the fundamental ontology that forms the unified description framework is determined. Third, the mapping relationship between the real-time condition data and the model of manufacturing equipment capability ontology is established. On the basis of the mapping relationship, the knowledge structure of the manufacturing equipment capability ontology is able to update in real-time. Finally, a prototype system is developed to validate the feasibility of the proposed dynamic modeling method. The system implementation demonstrates that the proposed knowledge description framework and method are capable of reflecting the current conditions and the dynamic capability of manufacturing equipment.
Original languageEnglish
Article numberMANU-14-1536
JournalJournal of Manufacturing Science and Engineering
Issue number4
Early online date8 Jul 2015
Publication statusPublished - 1 Aug 2015


  • cloud manufacturing, manufacturing equipment capability, ontology, OWL, dynamic modeling


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